24 citations · 57 across the 43 of their papers we have counts for
52 papers
Revenue Guarantee Equivalence between Dominant-Strategy and Bayesian Mechanisms
Nir Bachrach, Yi-Chun Chen, Inbal Talgam-Cohen +2
In auction design with limited information about bidders' value distributions, we provide an optimality foundation for dominant-strategy mechanisms. We show that simple dominant-st…
An Introduction to Contract Theory for Computer Scientists
Paul Duetting, Michal Feldman, Inbal Talgam-Cohen
This survey introduces contract design to computer scientists: using outcome-based payments to incentivize effort. We discuss applications that motivate a computational approach to…
Ex-ante versus Ex-post: Egalitarian Facility Location Mechanism Design
Zohar Barak, Inbal Talgam-Cohen
We study the facility location mechanism design problem where strategic agents report locations in Euclidean space and the mechanism outputs a single facility location. Each ag…
Optimal Auction Design for Constrained Buyers
Batya Berzack, Rotem Oshman, Inbal Talgam-Cohen
We study single-parameter, multi-buyer auctions in which buyers are subject to constraints that affect their bidding strategy. Such constraints arise in many real-world auction set…
Teaming Up with AI: Coordination and Cooperation
Nicole Immorlica, Inbal Talgam-Cohen
Successful diffusion of AI in the workforce hinges on the economic value that AI brings to human endeavors. Bringing AI into the workforce is more than deploying a powerful new tec…
ZEBRA: Zero-shot Budgeted Resource Allocation for LLM Orchestration
May Hamri, Inbal Talgam-Cohen
As autonomous agents increasingly execute end-to-end tasks under fixed monetary budgets, the pressing open question shifts from whether the budget is respected, to how to spend it…
Adaptive Contracts for Cost-Effective AI Delegation
Eden Saig, Tamar Garbuz, Ariel D. Procaccia +2
When organizations delegate text generation tasks to AI providers via pay-for-performance contracts, expected payments rise when evaluation is noisy. As evaluation methods become m…
Online Contract Design
Elad Lavi, Hadas Shachnai, Inbal Talgam-Cohen
We initiate the study of online contracts, which integrate the game-theoretic considerations of economic contract theory, with the algorithmic and informational challenges of onlin…
Approximating Pandora's Knapsack via Simple Policies
Zohar Barak, Asnat Berlin, Ilan Reuven Cohen +3
We introduce Pandora's Knapsack: a hybrid between the classic stochastic knapsack problem [Dean et al., 2008] and Pandora's box [Weitzman, 1979]. As in stochastic knapsack, items h…
An Algorithm-to-Contract Framework without Demand Queries
Ilan Doron-Arad, Hadas Shachnai, Gilad Shmerler +1
Consider costly and time-consuming tasks that add up to the success of a project, and must be fitted into a given time-frame. This is an instance of the classic budgeted maximizati…
Multi-Project Contracts
Tal Alon, Matteo Castiglioni, Junjie Chen +3
We study a new class of contract design problems where a principal delegates the execution of multiple projects to a set of agents. The principal's expected reward from each projec…
Dynamic Rental Games with Stagewise Individual Rationality
Batya Berzack, Rotem Oshman, Inbal Talgam-Cohen
We study \emph{rental games} -- a single-parameter dynamic mechanism design problem, in which a designer rents out an indivisible asset over days. Each day, an agent arrives wi…
Welfare and Beyond in Multi-Agent Contracts
Gil Aharoni, Martin Hoefer, Inbal Talgam-Cohen
A principal delegates a project to a team from a pool of agents. The project's value if all agents in exert costly effort is . To incentivize the agents to partic…
Algorithmic Contract Theory: A Survey
Paul Duetting, Michal Feldman, Inbal Talgam-Cohen
A contract is an economic tool used by a principal to incentivize one or more agents to exert effort on her behalf, by defining payments based on observable performance measures. A…
Principal-Agent Reinforcement Learning: Orchestrating AI Agents with Contracts
Dima Ivanov, Paul Dütting, Inbal Talgam-Cohen +2
The increasing deployment of AI is shaping the future landscape of the internet, which is set to become an integrated ecosystem of AI agents. Orchestrating the interaction among AI…
Incentivizing Quality Text Generation via Statistical Contracts
Eden Saig, Ohad Einav, Inbal Talgam-Cohen
While the success of large language models (LLMs) increases demand for machine-generated text, current pay-per-token pricing schemes create a misalignment of incentives known in ec…
Statistically Truthful Auctions via Acceptance Rule
Roy Maor Lotan, Inbal Talgam-Cohen, Yaniv Romano
Auctions are key for maximizing sellers' revenue and ensuring truthful bidding among buyers. Recently, an approach known as differentiable economics based on machine learning (ML)…
MAC Advice for Facility Location Mechanism Design
Zohar Barak, Anupam Gupta, Inbal Talgam-Cohen
Algorithms with predictions have attracted much attention in the last years across various domains, including variants of facility location, as a way to surpass traditional worst-c…
Contracting with a Learning Agent
Guru Guruganesh, Yoav Kolumbus, Jon Schneider +4
Many real-life contractual relations differ completely from the clean, static model at the heart of principal-agent theory. Typically, they involve repeated strategic interactions…
Algorithmic Cheap Talk
Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu +1
The literature on strategic communication originated with the influential cheap talk model, which precedes the Bayesian persuasion model by three decades. This model describes an i…
Deep Contract Design via Discontinuous Networks
Tonghan Wang, Paul Dütting, Dmitry Ivanov +2
Contract design involves a principal who establishes contractual agreements about payments for outcomes that arise from the actions of an agent. In this paper, we initiate the stud…
Delegated Classification
Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld
When machine learning is outsourced to a rational agent, conflicts of interest might arise and severely impact predictive performance. In this work, we propose a theoretical framew…
A Random Dictator Is All You Need
Itai Arieli, Yakov Babichenko, Inbal Talgam-Cohen +1
We study information aggregation with a decision maker aggregating binary recommendations from symmetric agents. Each agent's recommendation depends on her private information abou…
Approximate Optimality of Linear Contracts Under Uncertainty
Tal Alon, Paul Dütting, Yingkai Li +1
We consider a hidden-action principal-agent model, in which actions require different amounts of effort, and the agent privately knows his ability that determines his cost of effor…